BARILLOT Emmanuel

Molecular and phenotypic data about tumors and models are accumulating at an ever-increasing pace, and is becoming a routine source of information in the medical setting, thanks to lowering costs and improved biotechnological devices (DNA sequencing, mass spectrometry, imaging…). As a consequence, the bottleneck in cancer research has shifted from data acquisition to computational analysis. We still lack powerful computational models and analytical approaches to convert our deepened observations into full understanding of the biology of cancer and to optimize the benefit for patients. My work at the intersection of molecular oncology, mathematical modeling and machine learning is designed to overcome these limitations.

BARILLOT Emmanuel